Titulares de las redacciones y blogs que seguimos.
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Learn how i14 trained and served Laplace 3B, a linear attention model, on AWS Trainium2 using native PyTorch. Its recurrent state stays fixed at 29.5 MB per sequence regardless of context length, avoiding the growing key-value cache of transformer models and keeping serving memory predictable.
SpaceX’s data centers and Grok agents have been more profitable than investors expected in second quarter of the year, as the company leaves its roots…
OpenAI says it's adding Orchestra's team and technology to work on Rosalind, its AI model for life sciences research, and to its related Rosalind Workbench…
Learn how Runpod autoscaling helps teams cut costs and improve performance for both training and inference. Includes best practices and real-world.
Learn how to build ethical AI, from bias and privacy to transparency and sustainability, using tools and infrastructure that support responsible work.
This tutorial guides users through setting up a true SSH daemon on Runpod, enabling functionalities like SCP and IDE connections. It covers selecting a.
Learn how to fine-tune large language models using Axolotl on Runpod. This guide covers LoRA, 8-bit quantization, DeepSpeed, and GPU infrastructure setup.
Learn how to reduce LLM inference costs and latency using quantization, vLLM, SGLang, and speculative decoding without upgrading your hardware.
From Mistral to DeepSeek, open-source AI is closing the gap with closed models, and, in some cases, outperforming them. Here's why builders are betting on.
Explore what's possible when training Flux.1 Dev on AMD's 192GB MI300X GPU. This post dives into fine-tuning at scale with huge batch sizes and real-world.
Big labs may dominate the headlines, but the future of AI is being shaped by indie devs, fast-moving builders shipping small, weird, brilliant things.
A practical guide to calculating VRAM for full-parameter fine-tuning, with equations to size your compute and why inference rules of thumb fall short.
Google has joined Amazon in releasing a developer tool that makes it easy for PyTorch users to move their apps off Nvidia GPUs.
The company says the feature is designed for situations where users might be discussing something personal or planning a surprise and want to keep those…
Meta says it paused a Muse feature that lets you share conversations with the AI assistant after researchers found the URLs publicly available on the…
The Smartsheet Model Context Protocol (MCP) Server lets AI agents read, update, and act on live data. This post shows two ways to connect it on AWS: Amazon Quick for business teams and Kiro for developers, so your agents can work with Smartsheet without switching tools.
The Smartsheet Model Context Protocol (MCP) Server lets AI agents read, update, and act on live work management data. This post shows two ways to connect it on AWS: Amazon Quick for business teams and Kiro for developers, so your agents can work with Smartsheet without switching tools.
The former Google CEO owns about 1% stake in the leading AI lab, Bloomberg reported.
Enterprise supply chains are data-rich but insight-poor, with the data to decide scattered across ERP, monitoring, procurement, and email. This post shows how Amazon Bedrock AgentCore exposes those systems as a governed tool layer, and how Amazon Quick turns them into one conversational experience for business users, with a deploy-it-yourself walkthrough.
